• 한국지반환경공학회 논문집
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• 제6권4호
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• pp.59-64
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• 2005

근래 건설현장에서의 연약처리문제는 자주 대두되는 문제이며, 이러한 연약지반을 개량하기 위한 고압분사공법은 없어서는 아니될 필수적인 공법이지만 적용에 있어서 보강효과미흡, 지하수 및 지반오염문제 등 해결해야할 선결문제가 있다. MJM(Mortar Jet Method)공법은 주입재료로서 기존의 시멘트 외에 모래를 혼합하여 획기적 강도증대가 가능하며 3중관으로서, 슬라임 배출을 용이하게 하는 노즐을 부착시켜 치환율을 높여 전단면이 균질한 주상형고결체를 형성시킬 수 있고 특히, 해성점토 지반에서 기초말뚝으로서의 활용이 기대된다. 본 연구에서는 MJM공법의 실내 시험 및 현장시험시공을 통해 현장 적용성을 검토하였다.

• Corrosion Science and Technology
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• 제15권1호
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• pp.18-27
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• 2016

In this study, the accelerated corrosion test by combined deteriorating action of salt damage and freeze-thaw was investigated. freeze-thaw cycle is one method for corrosion testing; corrosion initiation time was measured in four types of concrete samples, i.e., two samples mixed with fly ash (FA) and blast furnace slag (BS), and the other two samples having two water/cement ratio (W/C = 0.6, 0.35) without admixture (OPC60 and OPC35). The corrosion of rebar embedded in concrete occurred most quickly at the $30^{th}$ freeze-thaw cycle. Moreover, a corrosion monitoring method with a half-cell potential measurement and relative dynamic elastic modulus derived from resonant frequency measures was conducted simultaneously. The results indicated that the corrosion of rebar occurred when the relative dynamic elastic modulus was less than 60%. Therefore, dynamic elastic modulus can be used to detect corrosion of steel bar. The results of the accelerated corrosion test exhibited significant difference according to corrosion periods combined with each test condition. Consequently, the OPC60 showed the lowest corrosion resistance among the samples.

• Computers and Concrete
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• 제15권4호
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• pp.503-514
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• 2015

Fibre-added concretes are frequently used in large site applications such as slab and airports as well as in bearing system elements or prefabricated elements. It is very difficult to determine the mechanical properties of the fibre-added concretes by experimental methods in situ. The purpose of this study is to develop an artificial neural network (ANN) model in order to predict the compressive and bending strengths of hybrid fibre-added and non-added concretes. The strengths have been predicted by means of the data that has been obtained from destructive (DT) and non-destructive tests (NDT) on the samples. NDTs are ultrasonic pulse velocity (UPV) and Rebound Hammer Tests (RH). 105 pieces of cylinder samples with a dimension of $150{\times}300mm$, 105 pieces of bending samples with a dimension of $100{\times}100{\times}400mm$ have been manufactured. The first set has been manufactured without fibre addition, the second set with the addition of %0.5 polypropylene and %0.5 steel fibre in terms of volume, and the third set with the addition of %0.5 polypropylene, %1 steel fibre. The water/cement (w/c) ratio of samples parametrically varies between 0.3-0.9. The experimentally measured compressive and bending strengths have been compared with predicted results by use of ANN method.

• Computers and Concrete
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• 제10권4호
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• pp.409-417
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• 2012

The quality of high performance concrete largely depends on water cement ratio, porosity, material composition and mix methods. The uniformity of color, texture and compressive strengths are quality indicators commonly used to assess the overall characteristics of concrete mixes. The homogeneity and share of coarse aggregates play a key role in concrete quality and must be analyzed in a microscopic point of view. This research studies the quality of high performance concrete by taking drilled cores in both horizontal and vertical directions from a 1.0 $m^3$ specimen. The coarse aggregate, expressed in digitized $100{\times}116$ dpi resolution images are processed based on brightness in colors through commercial software converted into text files. With the image converting to text format, the share of coarse aggregate is quantified leading to a satisfactory assessment of homogeneity - a quality index of high performance concrete. The compressive strengths of concrete and the shares of coarse aggregate of the samples are also compared in this research study to illustrate its correlation in concrete quality. It is concluded that a higher homogeneity of aggregate exists in the vertical plane than that of the horizontal planes of the high performance concrete. In addition, the concrete specimen showing denser particle packing has relatively higher compressive strengths. The research methodology provides an easy-to-use, direct measurement of high performance concrete when conducting quality assessment in the construction site.

• 한국해양공학회지
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• 제15권1호
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• pp.57-66
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• 2001

In order to measure steel corrosion in mortar by a transient electro-magnetic (TEM) Method, the development of the sensors have been studied. The sensors were made of enamelled wire with diameter of 0.25mm and Acril. The sensor configuration was used as a coincident loop type. The secondary electro motive force(EMF) was measured with SIROTEM III. The accelerator was equipped with the SIROTEM III. The accelerator permits the transmitter to turn off approximately 10~15 times faster than normal. The high resolution time series used for very shallow or high resistivity investigation was selected. The steels were embedded in mortar which were made from sand : cement : water ratio of 2 : 1: 0.5. The mortar specimen was 50cm long, 20cm wide and 10cm thick. To investigate steel corrosion in mortar, the sensors used were with 2$\times$2$cm^2$(3, 6, 9$\Omega$), 3$\times$3$cm^2$(3, 6, 9$\Omega$) and 6$\times$6$cm^2$(3, 6, 9$\Omega$). The obtained result obtained showed that the sensor 8(6$\times$6$cm^2$, 6$\Omega$) was the proper sensor for the measurement of steel corrosion in mortar.

• Structural Engineering and Mechanics
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• 제68권6호
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• pp.691-700
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• 2018

Ground granulated blast furnace slag (GGBS) is a by product obtained from iron and steel industries, useful in the design and development of high quality cement paste/mortar and concrete. This paper investigates the applicability of relevance vector machine (RVM) based regression model to predict the compressive strength of various GGBS based concrete mixes. Compressive strength data for various GGBS based concrete mixes has been obtained by considering the effect of water binder ratio and steel fibres. RVM is a machine learning technique which employs Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM is an extension of support vector machine which couples probabilistic classification and regression. RVM is established based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Compressive strength model has been developed by using MATLAB software for training and prediction. About 70% of the data has been used for development of RVM model and 30% of the data is used for validation. The predicted compressive strength for GGBS based concrete mixes is found to be in very good agreement with those of the corresponding experimental observations.

• Advances in concrete construction
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• 제8권1호
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• pp.55-64
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• 2019

Chloride corrosion has become the main factor of reducing the service life of reinforced concrete structures. The object of this paper is to propose a theoretical model that predicts the service life of chloride-corrosive concrete under fatigue load. In the process of modeling, the concrete is divided into two parts, microcrack and matrix. Taking the variation of mcirocrack area caused by fatigue load into account, an equation of chloride diffusion coefficient under fatigue load is established, and then the predictive model is developed based on Fick's second law. This model has an analytic solution and is reasonable in comparison to previous studies. Finally, some factors (chloride diffusion coefficient, surface chloride concentration and fatigue parameter) are analyzed to further investigate this model. The results indicate: the time to pit-to-crack transition and time to crack growth should not be neglected when predicting service life of concrete in strong corrosive condition; the type of fatigue loads also has a great impact on lifetime of concrete. In generally, this model is convenient to predict service life of chloride-corrosive concrete with different water to cement ratio, under different corrosive condition and under different types of fatigue load.

• Computers and Concrete
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• 제24권2호
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• pp.137-150
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• 2019

In this paper, surrogate models such as multivariate adaptive regression splines (MARS) and M5P model tree (M5P MT) methods have been investigated in order to propose a new formulation for the 28-days compressive strength of self-compacting concrete (SCC) incorporating metakaolin as a supplementary cementitious materials. A database comprising experimental data has been assembled from several published papers in the literature and the data have been used for training and testing. In particular, the data are arranged in a format of seven input parameters covering contents of cement, coarse aggregate to fine aggregate ratio, water, metakaolin, super plasticizer, largest maximum size and binder as well as one output parameter, which is the 28-days compressive strength. The efficiency of the proposed techniques has been demonstrated by means of certain statistical criteria. The findings have been compared to experimental results and their comparisons shows that the MARS and M5P MT approaches predict the compressive strength of SCC incorporating metakaolin with great precision. The performed sensitivity analysis to assign effective parameters on 28-days compressive strength indicates that cementitious binder content is the most effective variable in the mixture.

• Advances in concrete construction
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• 제7권3호
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• pp.143-150
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• 2019

This study presents the fracture properties of nano modified medium strength concrete (MSC). The nano particle used in this study is nano silica which replaces cement about 1 and 2% by weight, and the micro steel fibers are added about 0.4% volume of concrete. In addition to fracture properties, mechanical properties, namely, compressive strength, split tensile strength, and flexural strength of nano modified MSC are studied. To ensure the durability of the MSC, durability studies such as rapid chloride penetration test, sorptivity test, and water absorption test have been carried out for the nano modified MSC. From the study, it is observed that significant performance improvement in nano modified MSC in terms of strength and durability which could be attributed due to the addition pozzolanic reaction and the filler effect of nano silica. The incorporation of nano silica increases the fracture energy about 30% for mix without nano silica. Also, size independent fracture energy is arrived using two popular methods, namely, RILEM work of fracture method with $P-{\delta}$ tail correction and boundary effect method. Both the methods resulted in nearly the same size-independent $G_F$ irrespective of the notch to depth ratio of the same specimen. This shows evidence that either of the two procedures could be used in practice for analysis of cracked concrete structures.

• Advances in materials Research
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• 제11권1호
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• pp.75-90
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• 2022

In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set.